Problem of the Day  What do you get when you cross a mountain climber and a grape?

Problem of the Day  What do you get when you cross a mountain climber and a grape?  Nothing, you cannot cross a scalar.

CSC 212 – Data Structures

Using Stack

public interface Stack extends Collection { public E top() throws EmptyStackException; public E pop() throws EmptyStackException; public void push(E element); }  Any type of data stored within a Stack  Generics enable us to avoid rewriting this code  Minimum set of exceptions defined by interface  Classes could throw more unchecked exceptions Stack Interface

Array-based Implementation  Array reference in a field  Another field tracks top element’s index  Stack size also: top + 1  Add to next lowest index  Remove highest index Algorithm isEmpty() return top == -1 Algorithm pop() if isEmpty() then throw new EmptyStackException else top  top  1 return S[top + 1] 012 … ArrayStack S top  -1

Array-based Implementation  Array reference in a field  Another field tracks top element’s index  Stack size also: top + 1  Add to next lowest index  Remove highest index Algorithm isEmpty() return top == -1 Algorithm pop() if isEmpty() then throw new EmptyStackException else top  top  1 return S[top + 1] 012 top … ArrayStack S top  -1

top Array-based Implementation  Array reference in a field  Another field tracks top element’s index  Stack size also: top + 1  Add to next lowest index  Remove highest index Algorithm isEmpty() return top == -1 Algorithm pop() if isEmpty() then throw new EmptyStackException else top  top  1 return S[top + 1] ArrayStack S top  X 012 … X

Array-based Implementation  Array reference in a field  Another field tracks top element’s index  Stack size also: top + 1  Add to next lowest index  Remove highest index Algorithm isEmpty() return top == -1 Algorithm pop() if isEmpty() then throw new EmptyStackException else top  top  1 return S[top + 1] ArrayStack S top  (X -1) 012 … X top

 Could fill array with data  More push() s impossible  Throw exception on error  Specific to array-based  Unchecked exception must be used Algorithm push(elem) if top == S.length  1 then throw new FullStackException else top  top + 1 S[top]  elem fi ArrayStack S top  (X -1) 012 … X top

 Could fill array with data  More push() s impossible  Throw exception on error  Specific to array-based  Unchecked exception must be used Algorithm push(elem) if top == S.length  1 then throw new FullStackException else top  top + 1 S[top]  elem fi ArrayStack S top  X 012 … X top

 Could fill array with data  More push() s impossible  Throw exception on error  Specific to array-based  Unchecked exception must be used Algorithm push(elem) if top == S.length  1 then throw new FullStackException else top  top + 1 S[top]  elem fi ArrayStack S top  S.length … top

Oops… My Bad  Could fill array with data  More push() s impossible  Throw exception on error  Specific to array-based  Unchecked exception must be used Algorithm push(elem) if top == S.length  1 then throw new FullStackException else top  top + 1 S[top]  elem fi ArrayStack S top  S.length … top

Array-based Stack Why It RocksWhy It Sucks  Easy to write & read  Simple to find bugs  Quick running times  Methods take O(1) time huge  Array must be huge  Max. possible elements  Problems occur when too many exist at once  When full, throws specific exception

Better Approach (Maybe?)  Implement Stack using linked list  Grows & shrinks as elements added & removed  Add element in push() by allocating a Node  pop() removes Node s from linked list in  Concerns about size limits are forgotten

Once You pop() …  Check for empty Stack  If it is, throw exception  Pop the top Node  Node ’s element saved  top moved to next Node  Algorithm pop() if isEmpty() then throw new EmptyStackException else retVal  top.getElement() top  top.getNext() size  size - 1 fi return retVal NodeStack size  6 top

 Once You pop() …  Check for empty Stack  If it is, throw exception  Pop the top Node  Node ’s element saved  top moved to next Node retVal Algorithm pop() if isEmpty() then throw new EmptyStackException else retVal  top.getElement() top  top.getNext() size  size - 1 fi return retVal NodeStack size  6 top

 Once You pop() …  Check for empty Stack  If it is, throw exception  Pop the top Node  Node ’s element saved  top moved to next Node retVal Algorithm pop() if isEmpty() then throw new EmptyStackException else retVal  top.getElement() top  top.getNext() size  size - 1 fi return retVal NodeStack size  6 top

 Once You pop() …  Check for empty Stack  If it is, throw exception  Pop the top Node  Node ’s element saved  top moved to next Node retVal Algorithm pop() if isEmpty() then throw new EmptyStackException else retVal  top.getElement() top  top.getNext() size  size - 1 fi return retVal NodeStack size  5 top

 Linked list-based Stack  push ing very easy, too  Adds new top node  Easy to check if empty  Simplified w/o sentinel Algorithm push(e) newN  new Node(e, top) top  newN size  size + 1 Algorithm isEmpty() return top == null NodeStack size  5 top

 Linked list-based Stack  push ing very easy, too  Adds new top node  Easy to check if empty  Simplified w/o sentinel Algorithm push(e) newN  new Node(e, top) top  newN size  size + 1 Algorithm isEmpty() return top == null e NodeStack size  5 top

 Linked list-based Stack  push ing very easy, too  Adds new top node  Easy to check if empty  Simplified w/o sentinel Algorithm push(e) newN  new Node(e, top) top  newN size  size + 1 Algorithm isEmpty() return top == null newN NodeStack size  5 top e

 Linked list-based Stack  push ing very easy, too  Adds new top node  Easy to check if empty  Simplified w/o sentinel Algorithm push(e) newN  new Node(e, top) top  newN size  size + 1 Algorithm isEmpty() return top == null newN NodeStack size  5 top e

 Linked list-based Stack  push ing very easy, too  Adds new top node  Easy to check if empty  Simplified w/o sentinel Algorithm push(e) newN  new Node(e, top) top  newN size  size + 1 Algorithm isEmpty() return top == null NodeStack size  6 top

Your Turn  Get into your groups and complete activity

For Next Lecture  Read GT section 5.2 before Monday's class  Discusses design of the Queue ADT  Array-based implementation of Queue presented  Queue implementation of linked-list also shown  Week #8 weekly assignment due Tuesday  Programming Assignment #1 due next week